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@@ -394,6 +394,12 @@ before `run()`, the force will be reset to zero. For the common usage pattern
| `sim.load_checkpoint(path)` | Restore from HDF5 (config must match) | | `sim.load_checkpoint(path)` | Restore from HDF5 (config must match) |
| `sim.snapshot()` / `sim.restore()` | In-memory field snapshot | | `sim.snapshot()` / `sim.restore()` | In-memory field snapshot |
In-memory snapshots save populations only. Restore keeps the current clock,
controls, observations, geometry and flags; use it only while geometry is
unchanged. This is not a restart or an FSI rollback. In particular, do not
restore a snapshot taken before a translating circle changed position.
This geometry restriction is a caller precondition, not a runtime check.
#### Low-level access #### Low-level access
| Attribute | Description | | Attribute | Description |
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# Re_D = 50 Kármán inflow: paired pinball VIV / frozen PPO demo
Development experiment, frozen before results, 2026-10-31. No new production
method, structural damping, force filter, policy training, or main merge.
[Force-spike research index](research/moving_boundary_force_spikes.md).
## Plant and structure
Base `e9213dd2cc9cfed0e8487a3cf4ebdd94d23dc64d`; fixed-policy contract from
`580397eaf83c85b233495791ecc51662a374a247`. Reuse `steady_pinball` config,
coordinate map and exact held-force oscillator. D40, U=.005, nu=.004, MRT,
2559 x 1022, FP32 unshifted double buffers. Regularized parabolic inlet,
NEQ extrapolation outlet, bounce-back y walls (.5,1020.5); no BC changes.
D20 coordinates map x'=2x, y'=.5+2(y-.5).
Upstream cylinder (400,510.5), radius40, is static. Pinballs radius20 at
(1200,510.5), (1252,540.5), (1252,480.5) share only transverse translation.
Lab probes radius10 at (1600,590.5), (1600,510.5), (1600,430.5) stay fixed.
One shared `Translation`, travel ±D, max wall speed .025, existing clearance
and per-step move guards unchanged. M2: m*=2 based on all three disks,
M=7539.8223686, fn=.000025, K=.000186037660, C=zeta=0; release y=v=0.
Each native step uses previous-step sum(CME_y+Wen_y), then exact oscillator
update with held force. Wall speed is interval displacement y[n+1]-y[n].
Cover/uncover impulses are logged, never added to the selected RHS. This
estimator remains provisional; existing spike/convergence limitations remain.
## Same release state, two clocks
A static precursor retains the accepted Kármán sequence: upstream+probes,
2,048,000-step warmup, 150 x 3,200-step no-pinball target samples, add static
pinballs/sync, second 2,048,000-step warmup. Save both DDF buffers, flags,
clock and last instantaneous force. Construct each moving arm fresh at the
same zero-offset geometry, check flags, copy both buffers and clock, verify
exact copy hashes. This one-time research initialization is not a moving
checkpoint or FSI rollback. Initial policy observation and spin are zero.
Frozen model SHA256 `148240c1dcb8b11d8e5a0a9e991f6874c4e799c9744707bf0fb32a8efeb0468d`;
normalizer `534fda818c030a56960e95d0f3ac1e350d887d03db7f80f1d6453195a502b7f0`.
Only these explicit supplied assets are accepted. Policy is CPU deterministic.
Native policy signals: packed CME (same `read_force` path), lab area-mean
velocity, each averaged over SI3200. Convert to original D20 training units:
forces x2, area-mean velocity x2 x78, then frozen force-first normalization
and clipping. Fine-grid probe pixel footprint is not exactly identical;
using the original78 cells avoids a hidden area-count normalization change.
The moving plant, motion-induced force, lab-frame wake displacement and D40
resolution remain out of training distribution. No transfer guarantee.
A=(8a+(0,-4,4))*.005; EMA alpha=.9^(1/4), reset0 each SI; omega=+A_eff/20.
This preserves historical physical actuator timescale under dt/4.
The zero arm substitutes a=(0,.5,-.5), so all spins are identically zero.
Policy interval averaging does **not** average the native structural RHS.
## Bound, output, and interpretation
One serial pair, zero then controlled: 400SI=1,280,000 native steps=160D/U
=32Tn per arm. No retuning/automatic extension. Stop on nonfinite state,
no_donor, travel/speed/move rejection, or four-hour whole-pair wall cap.
A failure stops the remaining run; retain valid rows and completed intervals.
NaN trailing rows are unexecuted, not zero-valued observations.
Report first/last80D/U windows, mean offset separately from centered RMS,
half-range, peak, frequency and drift; native versus SI-averaged force,
CME/Wen/node/crossing terms and action/observation clipping. Last80D/U is
the principal descriptive window, not an asserted settled window. If zero
arm half-range <.1D there, classify weak response and do not claim vibration
suppression. Report continuous ratios regardless. Cloaking uses retained
canonical last30 lagged sensor DTW against this precursor's no-pinball target,
with fixed-body D20 results contextual only. These are development criteria,
not paper uncertainty, grid convergence, or proof of validated FSI.
Save native18-column rows (~184MB/arm), small SI signals, target, config,
release two buffers (~188MiB), hashes and terminal reports outside checkout.
No per-step field output. Expected new data <650MB, check actual resources.
```
CUDA_VISIBLE_DEVICES=0 PYTHONPATH=src python research/karman_viv/run.py \
--model /tmp/celeris-karman-viv-assets/model.zip \
--norm /tmp/celeris-karman-viv-assets/norm.json --out /tmp/NEW_OUTPUT
```
First `--smoke`: same D40 geometry, warmup32/target2x8/warmup32,
4x8 response steps each arm; strictly plumbing only. CPU source checks and
independent exact-tip review precede GPU. Preserve original DynamisLab files.
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@@ -30,6 +30,10 @@ cells (M1 `MovingCircleCells`), moving-wall Bouzidi with wall velocity
mass, eq_only, no_donor, crossings) accumulated since obs were zeroed; mass, eq_only, no_donor, crossings) accumulated since obs were zeroed;
`obs`/`read_force` keep their contract (CME on the body). `obs`/`read_force` keep their contract (CME on the body).
- `get_flags()` reads device flags back when moving circles exist. - `get_flags()` reads device flags back when moving circles exist.
- `snapshot()` / `restore()` save and restore populations only, keeping the
current clock, controls, observations, geometry and flags. Use them only
with unchanged geometry; restoring across a translation is unsupported
and is not rejected at runtime. They do not provide FSI rollback.
*Supported:* dense double buffer, D2Q9, FP32 unshifted, SRT/MRT, circles, *Supported:* dense double buffer, D2Q9, FP32 unshifted, SRT/MRT, circles,
spin. *Rejected before mutation:* EsoPull, ddf shifting, D3Q19, refinement / spin. *Rejected before mutation:* EsoPull, ddf shifting, D3Q19, refinement /
@@ -0,0 +1,99 @@
# Moving-boundary force spikes: evidence and source index
Updated 2026-10-31.
This note indexes supplied audited observations and primary-source extractions.
It does not report a newly measured cure or implement an alternative method.
Paper details below were supplied by the parent investigation; no new source
retrieval or independent paper verification was performed for this note.
## Current implementation and interpretation
- Celeris M1 reconstructs a fresh node as `feq(rho_bar, u_wall) + donor NEQ`.
- In exact arithmetic, the donor non-equilibrium component has zero mass and
momentum when formed against the donor's own equilibrium moments.
- Re-projecting that same reconstruction onto the same wall velocity therefore
does not, by itself, change its mass or momentum or supply a cure for spikes.
- Floating-point residuals should be measured separately from this algebraic fact.
- Peng's alternative differs upstream: extrapolate PDFs from three donors, then
replace selected moments. It is not simply another projection of current M1.
- PPO interval-force observations and native per-step FSI right-hand-side forces
are distinct signals; comparisons must identify which signal is being used.
## Audited run observations supplied to this note
- D40 revision: `e9213dd2cc9cfed0e8487a3cf4ebdd94d23dc64d`.
- Window: first `97.303 D/U` of physical time.
- Maximum displacement: `max |y|/D = 0.304893`.
- Maximum native force-coefficient increment: `max |ΔCy| = 0.66688`.
- D20 over the same physical-time window: `max |ΔCy| = 1.80735`.
- The largest D40 event involved 30 nodes.
- These are supplied audited observations, not measurements made for this note.
- Time steps and trajectories differ between runs. This comparison establishes
neither spatial convergence nor a unique cause for the force spikes.
Evidence locations supplied by the investigation:
- Horsea: `/tmp/celeris-results-pinball-resolution`.
- Mac: `validation-evidence/pinball-force-diagnosis`.
These locations index run evidence, not local copies of the cited papers.
## Tao, Hu, and Guo (2016): time-step decoupling
Computers & Fluids **133**, 1–14. DOI:
[10.1016/j.compfluid.2016.04.009](https://doi.org/10.1016/j.compfluid.2016.04.009).
[Publisher abstract](https://www.sciencedirect.com/science/article/pii/S0045793016301116).
- Abstract-level support only: non-equilibrium refill reduces oscillations.
- With local iteration, the compared refill methods give similar oscillation magnitudes.
- Time-step decoupling reduces oscillations further in the reported sedimentation,
Couette, and Poiseuille examples.
- The exact decoupling schedule and time-step ratios have not been verified.
- This abstract does not establish equivalence to an arbitrary force filter.
- Do not implement a claimed reproduction until the actual methods are available.
## Marson et al. (2021): local iterations
Physical Review E **103**, 053308. DOI:
[10.1103/PhysRevE.103.053308](https://doi.org/10.1103/PhysRevE.103.053308).
[Open repository record](https://archive-ouverte.unige.ch/unige:151868).
- §VI, p. 18 discusses pressure waves associated with fresh nodes.
- Appendix E.3, p. 25 and Fig. 18, p. 24 describe the local procedure.
- Copy a local sublattice, perform local collision and streaming, write the fresh
nodes, and repeat before the global collision and streaming operation.
- One to three iterations performed best in the reported tests; this is not a
universal iteration-count recommendation.
- The reported smoothed torque-noise assessment is qualitative here.
- Its thin-shell setting differs from the current moving-body configuration.
## Peng (2016): extrapolation and moment replacement
Computers & Mathematics with Applications **72**, 349–374. DOI:
[10.1016/j.camwa.2015.08.027](https://doi.org/10.1016/j.camwa.2015.08.027).
- §5.1.2, Eq. (50), p. 368: extrapolate PDFs along an outward normal direction:
`f_new(x) = 3 f(x + e) - 3 f(x + 2e) + f(x + 3e)`.
- §5.1.3, Eq. (51): wall equilibrium plus donor non-equilibrium is the family
containing the current M1 reconstruction.
- §5.1.4, Eqs. (52)–(54): in MRT space, replace momentum with `j = rho0 u_wall`,
preserve the other moments, then apply the inverse transform.
- A compressible Celeris adaptation must choose the appropriate density;
copying the paper's `rho0` blindly is not justified.
- Three valid donors require new eligibility checks and fallback behavior beyond
the current one-link shared-body clearance rule.
- §§5.2–5.3 retain nonzero fluctuations in specific configurations; these results
do not promise elimination of force spikes in the present problem.
## Bounded next investigation
1. Retain current M1 as the baseline and compare matched prescribed trajectories
over matched physical-time windows.
2. Record raw force RHS, node crossings, donor moments, mass and momentum changes,
impulse, spectra, and trajectory response together.
3. Evaluate local iterations, Peng-style reconstruction, and force filtering as
separate interventions, with explicit definitions and diagnostics.
4. Obtain the actual time-step-decoupling methods before implementing that method.
The current task indexes evidence only; it makes no alternative-method change.
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# Uncontrolled steady pinball: development protocol
Frozen before results: 1280 x 512 D2Q9/FP32/MRT, unshifted double buffer;
rho=1, mean U=.01, nu=.004, D=20, Re_D=50. Centres are (600,255.5),
(626,270.5), (626,240.5), radius10. No upstream cylinder. Passive probes stay
at (800,295.5), (800,255.5), (800,215.5), radius5. Every omega is zero.
Parabolic inlet, regularized NEQ damping1; y bounce-back planes .5/510.5;
NEQ-extrapolated outlet with backflow clamp (the configured blend is inactive in
this MRT route). Initial fluid is
parabolic equilibrium. Fixed warmup is 4 NX/U=512000 steps.
Geometry and fluid parameters follow DynamisLab 609116ec26f19766f5e9ce2b0df427d4e24faae8,
`legacy_test/core/legacy_env_builder.py:build_steady_cloak` and the retained
`config_lbm_pinball_legacy_re50d_u001.json`. This is a modern Celeris reconstruction,
not a bitwise Legacy reproduction: Legacy uses shifted incompressible MRT, a
different curved interpolation and prescribed parabolic outlet velocity. Current
Celeris uses standard MRT, two-branch BFL and extrapolated outlet velocity.
The fixed-hold control uses the SAME modern settings as the free case.
## Shared translation and ownership
`Translation(..., shared=True)` is explicitly transverse only. Reusing one
envelope INSTANCE declares common motion; equal but separate envelopes are not
linked. Before initialization and every positive Simulation.run, group members
must have identical applied offsets, effective target offsets and interval wall
velocities. Stage each member with set_body, then call run(1) once. An incomplete
or inconsistent target group is rejected before device uploads and can be fixed.
Existing pending-target direct-stepper restrictions remain.
Only members of that group may have overlapping whole swept bands. Their fixed
surface clearance must exceed4 lattice cells. This conservative bound exceeds
2 sqrt(2)+MAX_STEP = 3.329: M1 changed cells lie in old/new disks and read one-link
neighbors; M2 reads at most two links outside its new disk. Old/new relative
displacement is at most .5. Thus reads cannot reach another member's old/new
solid or M1 write region. M1 writes are disjoint. M2 writes opposite population
slots inside its own new disk, also disjoint. Separate first_slot ranges still
allocate each body's logical band/debug storage. Shared band cells alone do not
write anything: M1 returns unless membership changes; M2 returns unless a cut
link exists. Unrelated moving/static body and probe overlaps still reject.
This is a sufficient restricted-group condition, not support for near-contact
or independent motion. The r4, distance8.3, dy=.5 counterexample remains rejected.
CPU tests enumerate candidate donors/write footprints over subcell phases;
GPU tests compare fixed vs hold and member-order permutations through crossings
at wall speed .01 over the full +/-D envelope (8000 steps). The initial .5-speed
fixture failed with NaNs; a single-circle control also failed at step69. That
Mach~.866 fixture was unsuitable as a low-Mach numerical gate. Its failure is
retained; the geometric MAX_STEP proof is unchanged, not a stability guarantee.
CUDA kernels and arithmetic are unchanged.
## New structural parameters (not inherited from the paper)
One transverse state y,v; total assembly M=10 rho (3 pi D^2/4)=9424.77796,
fn=U/(5D)=.0001, Tn=10000, zeta=.01, K=M(2 pi fn)^2,
C=2 zeta M(2 pi fn). Initial y=v=0, no seed or later kick. Force is the sum
of the three instantaneous CME_y+Wen_y values from the previous fluid step;
node impulses are logged separately and never added. The damped oscillator is
integrated exactly for that piecewise-constant force over dt=1. Wall velocity
is y[n+1]-y[n], not the endpoint oscillator velocity. No filtering or retuning.
Observe600000 steps=60Tn=300 D/U after warmup, in each of free and fixed-hold
cases. Final20Tn is a descriptive comparison window; ten-Tn blocks expose drift.
No settled/periodic claim follows merely from reaching the cap. Stop on |y|>D,
nonfinite values, no_donor, rejected displacement or speed>.05. Report any quiet
response honestly. No automatic extension. --smoke uses32 warmup+32 steps only.
Native-step rows retain y,v, each body's CME/Wen/node terms and refill counters;
each600000x15 FP64 file is72MB. No full-field output or policy training. Compile
and run on one device serially, keep original outputs and dirty trees untouched.
This stage makes no claim of physical grid convergence or vibration suppression.
Run from checkout with PYTHONPATH=src and the existing Python environment:
`python research/steady_pinball/run.py --smoke --out <new-external-directory>`
then separately `--out <new-free-directory>` and `--fixed --out <new-fixed-directory>`.
## Zero-damping development follow-up (predeclared 2026-10-31)
The original d0bcefa run and its zeta=.01 results remain historical evidence.
The current runner exposes three fixed `--case` choices, all with C=0 as requested:
| Case | M / (rho 3 pi D^2/4) | fn | M | K | Purpose |
|---|---:|---:|---:|---:|---|
| Z0 | 10 | .0001 | 9424.77796 | .00372075320 | Remove damping only |
| M2 | 2 | .0001 | 1884.95559 | .000744150640 | Reduce mass and stiffness together at fixed fn |
| R2 | 2 | .00006 | 1884.95559 | .000267894231 | Change stiffness only relative to M2 |
R2 deliberately places fn at the retained fixed-body lift peak, f=.00006
(St=.12 on mean U). This is an informed development choice, not independent
physical validation or a promise of lock-in. All geometries, fluid settings,
512000-step fixed warmup, y0=v0=0, force time level and unfiltered RHS are unchanged.
No run result may select a replacement parameter or an automatic extension.
Each case has a 600000-step cap, the same 300 D/U physical duration. This equals
60 natural periods for Z0/M2 and 36 for R2. Compare the common final200000 native
steps, and six100000-step blocks, retaining actual natural/response frequencies
and ongoing drift. Do not call those blocks ten R2 periods. No settled-VIV claim
follows from a larger displacement. Report all three outcomes, including quiet
responses or stopped cases, alongside the existing fixed and damped-free records.
Unchanged stops: |y|>D, invalid move/speed, nonfinite values or no_donor. A 1800s
per-case wall cap and GPU headroom check bound resource use. Preserve partial rows;
do not add damping, clip trajectories, filter forces, or relax any stop. Each
case adds72MB of scalar history, no full fields. The separate Legacy/modern
baseline diagnosis does not change this FSI protocol.
## Matched D40 resolution comparison (predeclared 2026-10-31)
The first finer case is M2, with exactly the same mass ratio2, reduced velocity5,
zero structural damping, initial rest state and physical geometry as the retained
D20 M2. Targeting a development response of0.5--1D does not imply this case will
reach it. Do not change the structure within this comparison or discard a smaller
response. D60 is a supported scaling choice, not an automatically scheduled run.
For s=D/20 use dx'=dx/s, dt'=dt/s^2, U'=.01/s, nu'=.004, rho'=1,
fn'=fn/s^2, M'=s^2 M and K'=K/s^2. The same physical force per unit span
has F'_lat=F_lat/s. For D40 this gives U=.005, fn=.000025,
M=7539.82237, K=.000186037660, Re_D=50, and Tn=40000 steps.
The y walls are at .5 and ny-1.5, while x inlet/outlet source nodes are at0
and nx-1. Therefore map x'=s*x and y'=.5+s*(y-.5), with
nx'=s*(1280-1)+1, ny'=s*(512-2)+2. D40 uses2559x1022 and centres
(1200,510.5),(1252,540.5),(1252,480.5); every radius, probe and envelope scales
with D. The parabolic profile retains the same normalized wall coordinate.
This preserves the existing ghost-source boundary convention, without asserting
that it is an exact continuum open-boundary location.
Warmup=2048000 and response=2400000 native steps at D40: the SAME256 and300
D/U durations as D20, including60 natural periods after release. Compare the
six50-D/U blocks and the common final100-D/U window. Report max absolute y/D,
half-range, RMS, frequency and drift; peak-to-peak is not amplitude. No settling
claim follows from completion. Keep raw individual CME/Wen/node terms and all
crossing/fallback counters. Normalize net force by .5*rho*U^2*D in each case.
Report native crossing/non-crossing force increments separately, plus D40
four-step block means aligned with D20 intervals (diagnostic only, never replace
the raw spikes). Report final-window high-frequency variance above f*D/U=1,
using demeaned FFT Parseval weights, with the same physical cutoff for both cases.
Different motion histories confound spike-size comparisons; this is simultaneous
space/time/Mach refinement, not proof of a unique coarse-grid cause.
Only one full D40 M2 is initially scheduled, after CPU checks and a32+32-step
smoke. Stop on the unchanged geometry/speed/nonfinite/no_donor checks or a7200s
whole-case wall cap; save completed rows and status. The velocity cap scales to
.025 so its physical bound is unchanged. No force filtering, trajectory clipping,
automatic parameter search or extension. Scalar history is288MB; no full fields
or DDF snapshots are written. Two FP32 population buffers require about188MiB,
before flags, moving tables and context overhead; measure actual peak usage in
the smoke and full run. Keep all D20 outcomes. No production source changes.
Commands (one GPU and serial compilation, existing environment):
`python research/steady_pinball/run.py --case M2 --D 40 --smoke --out <new-smoke-dir>`
then `python research/steady_pinball/run.py --case M2 --D 40 --wall-seconds 7200 --out <new-full-dir>`.
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@@ -29,10 +29,17 @@ Claude, Grok and Astra at 1abfe954; implemented in research/viv_re150/.
- D = 40, MRT, dense double buffer; U_lat = .04, nu = U D / 150 = .010667, - D = 40, MRT, dense double buffer; U_lat = .04, nu = U D / 150 = .010667,
tau = .532. tau = .532.
- Box [0, 75 D] × [0, 60 D] (3000 × 2400) with the cylinder centre at - Nominal 75 D × 60 D lattice allocation (3000 × 2400), based on the
(30 D, 30 D): 30 D from the inlet, 45 D from the outlet, centred in y Kolahdouz §4.1.1 layout. Coordinate clarification of the existing run:
(Kolahdouz §4.1.1). Qin's own box ([0, 40 D] × [0, 20 D], centre (10 D, 10 D)) the driver uses `(30 D, (ny - 1)/2)` = `(1200, 1199.5)` in lattice
is the target paper's, not ours. coordinates, or `(30 D, 29.9875 D)`. The earlier `(30 D, 30 D)` wording
described the nominal box, not the exact executed centre.
Free-slip reflection planes are at `y = .5` and `y = ny - 1.5 = 2398.5`;
their separation is 2398 cells = 59.95 D, with the centre exactly midway,
29.975 D from each wall. Node counts are not physical wall-to-wall lengths.
This corrects the description, without changing the historical geometry
or results. Qin's own box ([0, 40 D] × [0, 20 D], centre (10 D, 10 D)) is
the target paper's, not ours.
- Boundaries: uniform Zou–He inlet, NEQ outlet (rho = 1, backflow clamp), - Boundaries: uniform Zou–He inlet, NEQ outlet (rho = 1, backflow clamp),
free-slip y walls. Kolahdouz uses a traction outlet: declared mismatch. free-slip y walls. Kolahdouz uses a traction outlet: declared mismatch.
- Qin's own VIV box (40 D × 20 D) is not used; a smaller box would be a - Qin's own VIV box (40 D × 20 D) is not used; a smaller box would be a
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@@ -8,6 +8,7 @@ s/T in [0.25 + (k-1), 0.25 + k); cycle 0 is the startup quarter.
from __future__ import annotations from __future__ import annotations
import math import math
from functools import lru_cache
import numpy as np import numpy as np
@@ -53,10 +54,16 @@ def bin_phase(s, T):
return None return None
@lru_cache(maxsize=8)
def _quadrature_rule(points):
"""Reuse the nodes and weights, which depend only on quadrature order."""
return np.polynomial.legendre.leggauss(points)
def interval_bases(n, T, points=16): def interval_bases(n, T, points=16):
"""Single-step interval averages over [n, n + 1] of cos phi |cos phi| and sin phi """Single-step interval averages over [n, n + 1] of cos phi |cos phi| and sin phi
(phi in radians = 2 pi s / T - pi / 2), Gauss-Legendre quadrature.""" (phi in radians = 2 pi s / T - pi / 2), Gauss-Legendre quadrature."""
x, w = np.polynomial.legendre.leggauss(points) x, w = _quadrature_rule(points)
s = int(n) % T + 0.5 * (x + 1.0) # periodic: identical bases in every cycle s = int(n) % T + 0.5 * (x + 1.0) # periodic: identical bases in every cycle
phi = 2.0 * np.pi * s / T - 0.5 * np.pi phi = 2.0 * np.pi * s / T - 0.5 * np.pi
c = np.cos(phi) c = np.cos(phi)
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@@ -0,0 +1,292 @@
"""One paired zero/PPO Karman pinball VIV experiment; see docs/karman_viv.md.
Research-only adapter: static precursor -> two fresh, identical moving plants.
No moving checkpoint/rollback, policy retraining, or force filtering.
"""
from __future__ import annotations
import argparse
import hashlib
import json
from pathlib import Path
import subprocess
import sys
import time
import numpy as np
ROOT = Path(__file__).resolve().parents[2]
sys.path.insert(0, str(ROOT))
from research.steady_pinball.run import Structure, config, scaled_points, CENTRES, PROBES, COLUMNS
BIAS = np.array([0., -4., 4.])
MODEL_SHA = '148240c1dcb8b11d8e5a0a9e991f6874c4e799c9744707bf0fb32a8efeb0468d'
NORM_SHA = '534fda818c030a56960e95d0f3ac1e350d887d03db7f80f1d6453195a502b7f0'
STEP_COLUMNS = (*COLUMNS, 'omega_F', 'omega_U', 'omega_L')
def sha(path):
h = hashlib.sha256()
with open(path, 'rb') as f:
for block in iter(lambda: f.read(1024*1024), b''):
h.update(block)
return h.hexdigest()
def array_sha(a):
return hashlib.sha256(memoryview(np.ascontiguousarray(a)).cast('B')).hexdigest()
def observation(sensor_mean, force_mean, scale, norm):
"""Fine-grid area means/CME -> trained D20 sensor sums/forces -> frozen norm."""
sensors = np.asarray(sensor_mean, np.float64)*scale*78.
forces = np.asarray(force_mean, np.float64)*scale
raw = np.asarray([*sensors, *forces], np.float32)
preclip = np.hstack((raw[6:]/norm['force_norm_fact'],
(raw[:6]-np.asarray(norm['sens_deviation'], np.float32)) /
np.asarray(norm['sens_norm_fact'], np.float32)))
if not np.isfinite(preclip).all():
raise RuntimeError('nonfinite policy observation')
return raw, np.clip(preclip, -1, 1).astype(np.float32), int((np.abs(preclip)>1).sum())
def wall_target(action, scale):
return (8.*np.asarray(action)+BIAS)*(.01/scale)
def ema(eff, target, scale):
alpha = .9**(1./scale**2)
return alpha*eff + (1.-alpha)*target
def load_policy(model):
# Same inference spaces as legacy_test.core.model_loader, without importing it.
import gymnasium as gym
from stable_baselines3 import PPO
class InferenceEnv(gym.Env):
observation_space = gym.spaces.Box(-1., 1., (12,), np.float32)
action_space = gym.spaces.Box(-1., 1., (3,), np.float32)
def reset(self, *, seed=None, options=None):
super().reset(seed=seed)
return np.zeros(12, np.float32), {}
def step(self, action):
return np.zeros(12, np.float32), 0., False, False, {}
return PPO.load(str(model), env=InferenceEnv(), device='cpu')
def add_scene(sim, scale, moving=False, pinball=True):
from CelerisLab.body.motion import Translation
sim.add_body('circle', scaled_points(((200., 255.5),), scale)[0], 20.*scale)
probes = [sim.add_body('sensor', c, 5.*scale) for c in scaled_points(PROBES, scale)]
bodies = []
if pinball:
envelope = Translation((0., 0., -20.*scale, 20.*scale), .05/scale, shared=True) if moving else None
bodies = [sim.add_body('circle', c, 10.*scale, translation=envelope)
for c in scaled_points(CENTRES, scale)]
return probes, bodies
def capture_seed(sim):
"""Capture both FP32 buffers at fixed geometry; never a moving-state checkpoint."""
import pycuda.driver as cuda
with sim.ctx.activate():
sim.stream.synchronize()
buffers = [np.empty_like(sim.field.ddf) for _ in range(2)]
for dst, src in zip(buffers, (sim.field.ddf_gpu, sim.field.temp_gpu)):
cuda.memcpy_dtoh(dst, src)
return (*buffers, sim.get_flags(), sim.stepper.step_count)
def install_seed(sim, seed):
"""Only a new, zero-offset instance may receive the static release state."""
import pycuda.driver as cuda
current, spare, flags, clock = seed
if sim.stepper.step_count != 0 or any(a.shape != sim.field.ddf.shape or a.dtype != sim.field.ddf.dtype
for a in (current, spare)):
raise ValueError('release transfer requires a fresh matching field')
if not np.array_equal(sim.get_flags(), flags):
raise ValueError('static/moving release flags differ')
for obj in sim.bodies.objects:
if obj.motion is not None and (obj.motion.applied != (0., 0.) or obj.motion.pending is not None):
raise ValueError('release transfer requires zero geometry and no target')
with sim.ctx.activate():
sim.stream.synchronize()
cuda.memcpy_htod(sim.field.ddf_gpu, current)
cuda.memcpy_htod(sim.field.temp_gpu, spare)
sim.stepper._step_count = clock # one-time research initialization, not restore()
sim.field.invalidate_host_ddf_cache()
copied = capture_seed(sim)
if copied[3] != clock or any(not np.array_equal(a, b, equal_nan=True) for a, b in zip(copied[:3], seed[:3])):
raise RuntimeError('release transfer did not preserve both buffers/flags')
return dict(current=array_sha(copied[0]), spare=array_sha(copied[1]), flags=array_sha(copied[2]), clock=copied[3])
def check_time(start, cap):
if time.monotonic()-start > cap:
raise TimeoutError('paired experiment wall cap')
def warmup(sim, count, start, cap):
while count:
check_time(start, cap)
n = min(count, 10000)
sim.run(n)
count -= n
def precursor(cfgpath, scale, warm, si, targets, out, start, cap):
from CelerisLab import Simulation
with Simulation(str(cfgpath)) as sim:
probes, _ = add_scene(sim, scale, pinball=False)
sim.initialize()
warmup(sim, warm, start, cap)
target = []
for _ in range(targets):
check_time(start, cap)
sim.run(si)
target.append([v*scale*78. for p in probes for v in sim.read_sensor(p)[:2]])
np.save(out/'target.npy', np.asarray(target, np.float32))
first = sim.bodies.count
for c in scaled_points(CENTRES, scale):
sim.add_body('circle', c, 10.*scale)
sim.sync_bodies()
bodies = list(range(first, first+3))
warmup(sim, warm-1, start, cap)
sim.run(1)
force = sum(float(sim.read_force(p)[1]) for p in bodies)
seed = capture_seed(sim)
np.savez(out/'release.npz', current=seed[0], spare=seed[1], flags=seed[2], clock=seed[3], force=force)
print(json.dumps(dict(event='precursor_complete', clock=seed[3], force=force,
elapsed_s=time.monotonic()-start)), flush=True)
return seed, force
def run_arm(name, cfgpath, scale, si, intervals, seed, initial_force, model, norm, out, start, cap):
from CelerisLab import Simulation
from CelerisLab.body.motion import MovingTables
cols = {k:i for i, k in enumerate(MovingTables.DIAG)}
diameter = 20.*scale
structure = Structure(2., 1.e-4/scale**2, 0., diameter)
arm = out/name
arm.mkdir()
rows = np.lib.format.open_memmap(arm/'steps.npy', mode='w+', dtype=np.float64,
shape=(si*intervals, len(STEP_COLUMNS)))
rows[:] = np.nan
signals = {k:np.full((intervals, width), np.nan, np.float32) for k, width in
[('sensors',6), ('forces',6), ('actions',3), ('observations',12)]}
completed = completed_intervals = clipped = 0
status, transfer = 'running', None
force = initial_force
obs = np.zeros(12, np.float32)
arm_start = time.monotonic()
try:
with Simulation(str(cfgpath)) as sim:
probes, bodies = add_scene(sim, scale, moving=True)
sim.initialize()
transfer = install_seed(sim, seed)
for i in range(intervals):
action = -BIAS/8 if name == 'zero' else np.asarray(model.predict(obs, deterministic=True)[0], np.float32)
if action.shape != (3,) or not np.isfinite(action).all() or (np.abs(action)>1).any():
raise RuntimeError('invalid policy action')
target, eff = wall_target(action, scale), np.zeros(3)
sensor_sum, force_sum = np.zeros(6), np.zeros(6)
for k in range(si):
if k % 1000 == 0:
check_time(start, cap)
y1, v1 = structure.candidate(force)
if not np.isfinite([y1,v1]).all() or abs(y1)>diameter:
raise RuntimeError('nonfinite structure or |y| > D; no retuning')
eff = ema(eff, target, scale)
omega = eff/(diameter/2)
for p, w in zip(bodies, omega):
sim.set_body(p, omega=float(w), offset=(0., y1), vy=y1-structure.y)
sim.run(1, zero_obs=True, sync_obs=True)
d = sim.moving_diagnostics()
cme, wen = d[:,cols['cme_y']], d[:,cols['wen_y']]
node = d[:,cols['cover_jy']]-d[:,cols['uncover_jy']]
row = (completed+1,y1,v1,*cme,*wen,*node,
d[:,cols['eq_only']].sum(),d[:,cols['no_donor']].sum(),d[:,cols['crossings']].sum(),*omega)
if not np.isfinite(row).all() or row[13] != 0:
raise RuntimeError('nonfinite moving diagnostic or no_donor')
f = np.array([v for p in bodies for v in sim.read_force(p)[:2]])
s = np.array([v for p in probes for v in sim.read_sensor(p)[:2]])
if not np.isfinite([f,s]).all():
raise RuntimeError('nonfinite force/sensor observation')
# Policy sees packed CME as in fixed-body training; structure sees CME+Wen.
force_sum += f
sensor_sum += s
force = float(cme.sum(dtype=np.float64)+wen.sum(dtype=np.float64))
rows[completed] = row
completed += 1
structure.y, structure.v = y1,v1
raw, obs, nclip = observation(sensor_sum/si, force_sum/si, scale, norm)
clipped += nclip
for key, val in [('sensors',raw[:6]),('forces',raw[6:]),('actions',action),('observations',obs)]:
signals[key][i] = val
completed_intervals = i+1
if (i+1)%10 == 0 or i+1 == intervals:
rows.flush()
np.savez(arm/'signals.npz', **signals)
print(json.dumps(dict(event='progress', arm=name, interval=i+1, step=completed,
tU_D=completed*.01/scale/diameter, y_D=y1/diameter,
elapsed_s=time.monotonic()-arm_start)), flush=True)
status = 'duration_completed_not_qualified'
except BaseException as exc:
status = f'error: {type(exc).__name__}: {exc}'
raise
finally:
rows.flush()
np.savez(arm/'signals.npz', **signals)
report = dict(status=status, completed_steps=completed, completed_intervals=completed_intervals,
elapsed_s=time.monotonic()-arm_start, release_transfer=transfer, clipped_observation_channels=clipped,
columns=STEP_COLUMNS, M=structure.mass,K=structure.stiffness,fn=structure.frequency,damping=0.,
max_abs_y_D=float(np.max(np.abs(rows[:completed,1]))/diameter) if completed else None)
(arm/'report.json').write_text(json.dumps(report,indent=2)+'\n')
def main():
ap = argparse.ArgumentParser(description=__doc__)
ap.add_argument('--model', type=Path, required=True)
ap.add_argument('--norm', type=Path, required=True)
ap.add_argument('--out', type=Path, required=True)
ap.add_argument('--smoke', action='store_true', help='short plumbing only; no physical conclusion')
ap.add_argument('--wall-seconds', type=float, default=14400.)
args = ap.parse_args()
if not np.isfinite(args.wall_seconds) or args.wall_seconds<=0:
ap.error('positive finite wall cap required')
if sha(args.model)!=MODEL_SHA or sha(args.norm)!=NORM_SHA:
ap.error('model/normalizer must match frozen provenance')
out = args.out.resolve()
if out == ROOT or ROOT in out.parents:
ap.error('output must be outside checkout')
out.mkdir(parents=True, exist_ok=False)
norm = json.loads(args.norm.read_text())
model = load_policy(args.model)
scale = 2.
warm, si, targets, intervals = (32,8,2,4) if args.smoke else (2048000,3200,150,400)
cfgpath = out/'config.json'
cfgpath.write_text(json.dumps(config(40),indent=2)+'\n')
receipt = dict(source=subprocess.check_output(['git','-C',str(ROOT),'rev-parse','HEAD'],text=True).strip(),
model_sha256=sha(args.model),norm_sha256=sha(args.norm),smoke=args.smoke,D=40,U=.005,nu=.004,
warmup_each=warm,target_intervals=targets,SI=si,response_intervals=intervals,
response_steps=si*intervals,response_tU_D=si*intervals*.005/40,
rhs='previous native step sum CME_y+Wen_y; policy uses interval packed CME',
probe_frame='lab-fixed; fine area mean * 2 * trained 78 cells',
ema_native_alpha=.9**.25, structural_damping=0., columns=STEP_COLUMNS)
(out/'case.json').write_text(json.dumps(receipt,indent=2)+'\n')
start = time.monotonic()
status = 'running'
try:
seed, force = precursor(cfgpath,scale,warm,si,targets,out,start,args.wall_seconds)
for name in ('zero','controlled'):
run_arm(name,cfgpath,scale,si,intervals,seed,force,model,norm,out,start,args.wall_seconds)
status = 'smoke_completed' if args.smoke else 'pair_completed_not_qualified'
except BaseException as exc:
status = f'error: {type(exc).__name__}: {exc}'
raise
finally:
(out/'terminal.json').write_text(json.dumps(dict(status=status,elapsed_s=time.monotonic()-start),indent=2)+'\n')
if __name__ == '__main__':
main()
+49
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@@ -0,0 +1,49 @@
{
"_doc": "Legacy geometry Re_D=50, U0=0.01, SI=800 baseline (kar_legacy_re50d_u001)",
"grid": {
"lattice_model": "D2Q9",
"nx": 1280,
"ny": 512,
"nz": 1
},
"physics": {
"data_type": "FP32",
"viscosity": 0.004,
"velocity": 0.01,
"rho": 1.0
},
"method": {
"collision": "MRT",
"streaming": "double_buffer",
"store_precision": "FP32",
"ddf_shifting": false,
"les": {
"enabled": false,
"cs": 0.16,
"closed_form": true
},
"trt": {
"magic_param": 0.1875
},
"inlet": {
"profile": "parabolic",
"scheme": "regularized",
"regularized_neq_damp": 1.0
},
"outlet": {
"mode": "neq_extrap",
"backflow_clamp": true,
"blend_alpha": 0.7,
"srt_neq_damp": 0.5
},
"y_wall_bc": "bounce_back",
"omega_guard": {
"min": 0.01,
"max": 1.99
}
},
"cuda": {
"threads_per_block": 256,
"compute_capability": "auto"
}
}
+196
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@@ -0,0 +1,196 @@
"""Uncontrolled paper-geometry steady Re_D=50, one transverse assembly DOF.
Three predeclared zero-damping structures; --smoke uses only 32 + 32 steps.
See docs/steady_pinball_fiv.md for historical solver differences and new structure.
"""
from __future__ import annotations
import argparse
import json
import math
from pathlib import Path
import subprocess
import time
import numpy as np
D, U, NU = 20., .01, .004
CENTRES = ((600., 255.5), (626., 270.5), (626., 240.5))
PROBES = ((800., 295.5), (800., 255.5), (800., 215.5))
WARMUP, STEPS, PERIOD = 512000, 600000, 10000
STRUCTURES = {'Z0': (10., 1.e-4), 'M2': (2., 1.e-4), 'R2': (2., 6.e-5)}
COLUMNS = ('step', 'y', 'v', 'cme_F', 'cme_U', 'cme_L', 'wen_F', 'wen_U', 'wen_L',
'node_F', 'node_U', 'node_L', 'eq_only', 'no_donor', 'crossings')
ROOT = Path(__file__).resolve().parents[2]
def config(diameter=D):
"""Diffusive refinement preserves the inlet/outlet and half-grid y walls."""
scale = diameter / D
if diameter not in (20, 40, 60):
raise ValueError('diameter must be 20, 40 or 60')
cfg = json.loads(Path(__file__).with_name('config.json').read_text())
cfg['grid']['nx'] = round((cfg['grid']['nx'] - 1) * scale + 1)
cfg['grid']['ny'] = round((cfg['grid']['ny'] - 2) * scale + 2)
cfg['physics']['velocity'] = U / scale
return cfg
def scaled_points(points, scale):
return tuple((scale*x, .5 + scale*(y-.5)) for x, y in points)
class Structure:
"""Exact damped oscillator update for a force held over dt=1; no force filter."""
def __init__(self, mass_ratio=10., frequency=1.e-4, zeta=0., diameter=D):
if not (math.isfinite(mass_ratio) and mass_ratio > 0. and
math.isfinite(frequency) and frequency > 0. and
math.isfinite(zeta) and 0. <= zeta < 1.):
raise ValueError('positive finite mass ratio/frequency and 0 <= zeta < 1 required')
self.mass_ratio, self.frequency = mass_ratio, frequency
self.mass = mass_ratio * 3. * math.pi * diameter * diameter / 4.
self.omega = 2. * math.pi * frequency
self.zeta = zeta
self.stiffness = self.mass * self.omega**2
self.damping = 2. * self.zeta * self.mass * self.omega
self.y = self.v = 0.
a = self.zeta * self.omega
wd = self.omega * math.sqrt(1. - self.zeta**2)
self.ec = math.exp(-a) * math.cos(wd)
self.es = math.exp(-a) * math.sin(wd) / wd
self.a = a
def candidate(self, force):
equilibrium = force / self.stiffness
z = self.y - equilibrium
return (equilibrium + (self.ec + self.a*self.es)*z + self.es*self.v,
-self.omega**2*self.es*z + (self.ec - self.a*self.es)*self.v)
def summarize(rows, diameter=D, block_steps=10*PERIOD):
windows = []
for start in range(0, len(rows), block_steps):
block = rows[start:start + block_steps]
fy = block[:, 3:9].sum(axis=1)
windows.append(dict(start_step=int(block[0, 0]), end_step=int(block[-1, 0]),
y_mean_D=float(block[:, 1].mean()/diameter),
y_rms_D=float(np.sqrt(np.mean(block[:, 1]**2))/diameter),
y_peak_D=float(np.abs(block[:, 1]).max()/diameter),
fy_mean=float(fy.mean()), fy_rms=float(np.sqrt(np.mean(fy**2))),
mean_power=float(np.mean(fy*block[:, 2]))))
return windows
def main():
ap = argparse.ArgumentParser(description=__doc__)
ap.add_argument('--out', required=True, type=Path)
ap.add_argument('--fixed', action='store_true', help='same modern moving-path geometry held fixed')
ap.add_argument('--smoke', action='store_true', help='32+32 steps, no physical result')
ap.add_argument('--case', choices=STRUCTURES, default='Z0',
help='predeclared structure; all cases have zero structural damping')
ap.add_argument('--D', type=int, choices=(20, 40, 60), default=20,
help='diameter in cells; diffusive scaling, matched geometry and physical duration')
ap.add_argument('--wall-seconds', type=float, default=7200., help='whole-case wall-clock cap')
args = ap.parse_args()
if not math.isfinite(args.wall_seconds) or args.wall_seconds <= 0:
ap.error('--wall-seconds must be finite and positive')
scale, time_scale = args.D / D, (args.D // int(D))**2
velocity = U / scale
centres, probes = scaled_points(CENTRES, scale), scaled_points(PROBES, scale)
period = PERIOD*time_scale
out = args.out.resolve()
if out == ROOT or ROOT in out.parents:
ap.error('output must be outside the checkout')
out.mkdir(parents=True, exist_ok=False)
cfg = config(args.D)
(out/'config.json').write_text(json.dumps(cfg, indent=2)+'\n')
source = subprocess.check_output(['git', '-C', str(ROOT), 'rev-parse', 'HEAD'], text=True).strip()
mass_ratio, frequency = STRUCTURES[args.case]
s = Structure(mass_ratio, frequency/time_scale, zeta=0., diameter=args.D)
warmup, count = (32, 32) if args.smoke else (WARMUP*time_scale, STEPS*time_scale)
rows = np.lib.format.open_memmap(out/'steps.npy', mode='w+', dtype=np.float64,
shape=(count, len(COLUMNS)))
rows[:] = np.nan
from CelerisLab import Simulation
from CelerisLab.body.motion import MovingTables, Translation
names = MovingTables.DIAG
col = {k: names.index(k) for k in names}
status, completed, f_last = 'running', 0, 0.
started = time.monotonic()
report = dict(source=source, case=args.case, fixed=args.fixed, smoke=args.smoke, columns=COLUMNS,
structure=dict(mass=s.mass, stiffness=s.stiffness, damping=s.damping,
mass_ratio_three_disks=s.mass_ratio,
zeta=s.zeta, fn=s.frequency, Tn=1./s.frequency, y0=0., v0=0.),
warmup_steps=warmup, requested_steps=count, dt=1., D=args.D, U=velocity, nu=NU,
relative_to_D20=dict(dx=1/scale, dt=1/time_scale),
centres=centres, probes=probes, wall_planes=(.5, cfg['grid']['ny']-1.5),
wall_cap_seconds=args.wall_seconds,
duration_Tn=count*s.frequency, duration_tU_D=count*velocity/args.D,
summary_block_steps=10*period,
rhs='sum of three instantaneous CME_y + Wen_y, one-step lag, no filtering')
try:
with Simulation(str(out/'config.json')) as sim:
# Match Legacy object order; probes remain passive and fixed in the lab.
for c in probes:
sim.add_body('sensor', c, 5.*scale)
envelope = Translation((0., 0., -args.D, args.D), .05/scale, shared=True)
bodies = [sim.add_body('circle', c, args.D/2, translation=envelope) for c in centres]
sim.initialize()
# At release obtain the last instantaneous force, not a warmup average.
remaining = warmup - 1
while remaining:
if time.monotonic()-started > args.wall_seconds:
raise TimeoutError('whole-case wall cap during warmup')
chunk = min(10000, remaining)
sim.run(chunk)
remaining -= chunk
sim.run(1)
d = sim.moving_diagnostics()
f_last = float(d[:, col['cme_y']].sum(dtype=np.float64) + d[:, col['wen_y']].sum(dtype=np.float64))
report['warmup_elapsed_s'] = time.monotonic()-started
print(json.dumps(dict(event='release', **report)), flush=True)
for n in range(count):
if n % 1000 == 0 and time.monotonic()-started > args.wall_seconds:
raise TimeoutError('whole-case wall cap during response')
y1, v1 = (0., 0.) if args.fixed else s.candidate(f_last)
if not all(map(math.isfinite, (y1, v1))) or abs(y1) > args.D:
status = 'stopped_nonfinite_or_travel_bound'
break
if not args.fixed:
for bid in bodies:
sim.set_body(bid, offset=(0., y1), vy=y1-s.y)
sim.run(1)
d = sim.moving_diagnostics()
cme, wen = d[:, col['cme_y']], d[:, col['wen_y']]
node = d[:, col['cover_jy']] - d[:, col['uncover_jy']]
row = (n+1, y1, v1, *cme, *wen, *node,
d[:, col['eq_only']].sum(), d[:, col['no_donor']].sum(), d[:, col['crossings']].sum())
if not np.isfinite(row).all() or row[-2] != 0:
status = 'stopped_nonfinite_or_no_donor'
break
rows[n] = row
completed = n+1
s.y, s.v = y1, v1
f_last = float(cme.sum(dtype=np.float64)+wen.sum(dtype=np.float64))
if completed % period == 0:
rows.flush()
print(json.dumps(dict(event='progress', step=completed, t_Tn=completed*s.frequency,
y_D=s.y/args.D, elapsed_s=time.monotonic()-started)), flush=True)
else:
status = 'smoke_completed' if args.smoke else 'duration_completed_not_qualified'
except BaseException as exc:
status = f'error: {type(exc).__name__}: {exc}'
raise
finally:
rows.flush()
report.update(status=status, completed_steps=completed, elapsed_s=time.monotonic()-started,
windows=summarize(rows[:completed], args.D, 10*period),
totals={key: float(rows[:completed, i].sum()) for key, i in
[('eq_only', 12), ('no_donor', 13), ('crossings', 14)]},
limitation='Uncontrolled development response only. No automatic settling, grid convergence, control or historical-solver equivalence claim.')
(out/'report.json').write_text(json.dumps(report, indent=2)+'\n')
print(json.dumps(report), flush=True)
if __name__ == '__main__':
main()
+4 -3
View File
@@ -1,8 +1,9 @@
"""One-shot predeclared VIV run (docs/validation/viv_re150_predeclare.md). """One-shot predeclared VIV run (docs/validation/viv_re150_predeclare.md).
Re 150, U* = 5, m/(rho D^2) = 2, zeta = 0, D = 40 on a 75 D x 60 D native Re 150, U* = 5, m/(rho D^2) = 2, zeta = 0, D = 40 on a nominal 75 D x 60 D
channel (uniform inlet, NEQ outlet, free-slip y walls), cylinder at lattice (uniform inlet, NEQ outlet, free-slip y walls). The cylinder is at
(30 D, 30 D). Structural RHS = CME + Wen (diagnostics: raw CME, node terms). (30 D, (ny - 1)/2); y-wall planes are .5 and ny - 1.5 in lattice coordinates.
Structural RHS = CME + Wen (diagnostics: raw CME, node terms).
Research driver only: Simulation API, no production change. Research driver only: Simulation API, no production change.
PYTHONPATH=src python research/viv_re150/run.py --out /path/outside/checkout PYTHONPATH=src python research/viv_re150/run.py --out /path/outside/checkout
+23
View File
@@ -14,6 +14,7 @@ from typing import Callable, Optional, Tuple
MAX_STEP = 0.5 # Euclidean centre displacement per step (lattice cells) MAX_STEP = 0.5 # Euclidean centre displacement per step (lattice cells)
BAND_MARGIN = 2 # cells added around the swept circle AABB BAND_MARGIN = 2 # cells added around the swept circle AABB
SHARED_CLEARANCE = 4.0 # > two diagonal links + MAX_STEP; docs/steady_pinball_fiv.md
R_MIN = 4.0 # smallest radius covered by the donor enumeration R_MIN = 4.0 # smallest radius covered by the donor enumeration
Vec = Tuple[float, float] Vec = Tuple[float, float]
@@ -31,6 +32,7 @@ class Translation:
"""Declared motion envelope: offset box (x_min, x_max, y_min, y_max) and speed bound.""" """Declared motion envelope: offset box (x_min, x_max, y_min, y_max) and speed bound."""
offset_box: Tuple[float, float, float, float] offset_box: Tuple[float, float, float, float]
max_speed: float max_speed: float
shared: bool = False # same envelope instance: synchronous transverse motion
def __post_init__(self): def __post_init__(self):
box = tuple(float(v) for v in self.offset_box) box = tuple(float(v) for v in self.offset_box)
@@ -41,10 +43,29 @@ class Translation:
raise ValueError("offset_box must contain the zero offset") raise ValueError("offset_box must contain the zero offset")
if not 0.0 < speed <= MAX_STEP: if not 0.0 < speed <= MAX_STEP:
raise ValueError(f"max_speed must satisfy 0 < max_speed <= {MAX_STEP}") raise ValueError(f"max_speed must satisfy 0 < max_speed <= {MAX_STEP}")
if self.shared and box[:2] != (0.0, 0.0):
raise ValueError("shared translation is transverse only (x offsets must be zero)")
object.__setattr__(self, "offset_box", box) object.__setattr__(self, "offset_box", box)
object.__setattr__(self, "max_speed", speed) object.__setattr__(self, "max_speed", speed)
def validate_shared_translations(circles):
"""Check common old/target offsets and wall velocities before device work.
Per-body setters may stage members in any order. Envelope identity (not
value equality) defines a group; a missing target means hold at applied.
"""
groups = {}
for motion in circles:
if not motion.translation.shared:
continue
target = motion.pending if motion.pending is not None else (motion.applied, (0.0, 0.0))
state = (motion.applied, target)
key = id(motion.translation)
if groups.setdefault(key, state) != state:
raise ValueError("shared translation needs identical applied/target offsets and velocities")
class MovingCircle: class MovingCircle:
"""Applied offset, pending target and the fail-closed commit of one circle.""" """Applied offset, pending target and the fail-closed commit of one circle."""
@@ -72,6 +93,8 @@ class MovingCircle:
x0, x1, y0, y1 = self.translation.offset_box x0, x1, y0, y1 = self.translation.offset_box
if not (x0 <= offset[0] <= x1 and y0 <= offset[1] <= y1): if not (x0 <= offset[0] <= x1 and y0 <= offset[1] <= y1):
raise ValueError(f"offset {offset} outside declared box {self.translation.offset_box}") raise ValueError(f"offset {offset} outside declared box {self.translation.offset_box}")
if self.translation.shared and velocity[0] != 0.0:
raise ValueError("shared translation needs zero x velocity")
step = math.hypot(offset[0] - self.applied[0], offset[1] - self.applied[1]) step = math.hypot(offset[0] - self.applied[0], offset[1] - self.applied[1])
if step > MAX_STEP: if step > MAX_STEP:
raise ValueError(f"per-step displacement {step} exceeds {MAX_STEP}") raise ValueError(f"per-step displacement {step} exceeds {MAX_STEP}")
+12
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@@ -259,6 +259,8 @@ class Simulation:
moving = self._moving_bodies() moving = self._moving_bodies()
if not moving: if not moving:
return return
from .body.motion import SHARED_CLEARANCE, validate_shared_translations
validate_shared_translations([obj.motion for obj in moving])
cfg = self.lbm_cfg cfg = self.lbm_cfg
if (not cfg.is_d2q9 or cfg.streaming != "double_buffer" or cfg.ddf_shifting if (not cfg.is_d2q9 or cfg.streaming != "double_buffer" or cfg.ddf_shifting
or cfg.store_precision != "FP32"): or cfg.store_precision != "FP32"):
@@ -277,6 +279,13 @@ class Simulation:
if other is obj: if other is obj:
continue continue
(cx, cy), r = other.center[:2], float(other.radius) (cx, cy), r = other.center[:2], float(other.radius)
if (other.motion is not None and obj.motion.translation.shared
and obj.motion.translation is other.motion.translation):
# Whole envelopes may overlap; simultaneous local stencils may not.
gap = np.hypot(obj.center[0] - cx, obj.center[1] - cy) - obj.radius - r
if gap <= SHARED_CLEARANCE:
raise ValueError("shared translation needs surface clearance > 4 cells")
continue
if other.motion is not None: if other.motion is not None:
ox0, ox1, oy0, oy1 = other.motion.band() ox0, ox1, oy0, oy1 = other.motion.band()
else: else:
@@ -719,6 +728,9 @@ class Simulation:
if steps < 0 or checkpoint_interval < 0: if steps < 0 or checkpoint_interval < 0:
raise ValueError("steps and checkpoint_interval must be nonnegative") raise ValueError("steps and checkpoint_interval must be nonnegative")
moving = self._moving_bodies() moving = self._moving_bodies()
if steps > 0 and moving:
from .body.motion import validate_shared_translations
validate_shared_translations([obj.motion for obj in moving])
if steps > 0 and moving and self.stepper.moving is None: if steps > 0 and moving and self.stepper.moving is None:
raise RuntimeError(MOVING_BLOCKED) raise RuntimeError(MOVING_BLOCKED)
if moving and checkpoint_interval > 0: if moving and checkpoint_interval > 0:
@@ -0,0 +1,62 @@
"""Small serial GPU gates for shared transverse circles; no physical benchmark."""
import json
from pathlib import Path
import numpy as np
from CelerisLab import Simulation
from CelerisLab.body.motion import MovingTables, Translation
CENTRES = ((70., 79.5), (96., 94.5), (96., 64.5))
def simulate(tmp_path, *, moving, offsets, reverse=False):
config = json.loads((Path(__file__).resolve().parents[2]/'research/steady_pinball/config.json').read_text())
config['grid'].update(nx=192, ny=160)
p = tmp_path/'config.json'
p.write_text(json.dumps(config))
with Simulation(str(p)) as sim:
envelope = Translation((0., 0., -20., 20.), .5, shared=True)
centres = list(reversed(CENTRES)) if reverse else list(CENTRES)
ids = [sim.add_body('circle', c, 10., translation=envelope if moving else None) for c in centres]
sim.initialize()
previous = 0.
crossings = 0.
for y in offsets:
if moving:
for bid in ids:
sim.set_body(bid, offset=(0., float(y)), vy=float(y-previous))
sim.run(1)
if moving:
diag = sim.moving_diagnostics()
assert np.isfinite(diag).all()
assert np.all(diag[:, MovingTables.DIAG.index('no_donor')] == 0)
crossings += diag[:, MovingTables.DIAG.index('crossings')].sum()
previous = y
forces = np.array([sim.read_force(bid) for bid in ids])
if reverse:
forces = forces[::-1]
return sim.get_ddf(), sim.get_flags(), forces, crossings
def test_fixed_vs_shared_hold(tmp_path):
fixed = simulate(tmp_path, moving=False, offsets=[0.]*32)
held = simulate(tmp_path, moving=True, offsets=[0.]*32)
assert np.array_equal(fixed[0], held[0], equal_nan=True)
assert np.array_equal(fixed[1], held[1])
# FP32 atomic force reduction order only; populations remain exactly equal.
np.testing.assert_allclose(fixed[2], held[2], rtol=0., atol=1e-4)
assert held[3] == 0
def test_common_motion_member_order_has_no_population_effect(tmp_path):
# MAX_STEP=.5 is a geometric bound, not a low-Mach stability guarantee.
# Keep the complete +/-D excursion at wall speed .01, equal to mean inflow.
offsets = np.concatenate((np.arange(1, 2001), np.arange(1999, -2001, -1),
np.arange(-1999, 1))) * .01
forward = simulate(tmp_path, moving=True, offsets=offsets)
reverse = simulate(tmp_path, moving=True, offsets=offsets, reverse=True)
assert forward[3] > 0 and forward[3] == reverse[3]
assert np.array_equal(forward[0], reverse[0], equal_nan=True)
assert np.array_equal(forward[1], reverse[1])
np.testing.assert_allclose(forward[2], reverse[2], rtol=0., atol=1e-4)
+29
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@@ -82,6 +82,35 @@ def test_interval_bases_and_morison_fit_recover_known_coefficients():
assert p.morison_fit(f, b[:, 0], b[:, 1]) == pytest.approx((2.09, 1.45), abs=1e-9) assert p.morison_fit(f, b[:, 0], b[:, 1]) == pytest.approx((2.09, 1.45), abs=1e-9)
def test_quadrature_rule_reused_across_steps_and_periods(monkeypatch):
original = np.polynomial.legendre.leggauss
orders = []
def counted(points):
orders.append(points)
return original(points)
p._quadrature_rule.cache_clear()
monkeypatch.setattr(np.polynomial.legendre, "leggauss", counted)
try:
for points in (16, 8, 16):
for period in (T, 2 * T):
for n in (0, 123, period + 123):
p.interval_bases(n, period, points)
assert orders == [16, 8]
finally:
p._quadrature_rule.cache_clear()
def test_interval_sine_basis_matches_exact_integral():
for period in (T, 2 * T):
half_width = math.pi / period
for n in (0, period // 4, period // 2, period - 1, 7 * period + 123):
midpoint = 2 * math.pi * ((n % period) + .5) / period - math.pi / 2
expected = math.sin(midpoint) * math.sin(half_width) / half_width
assert p.interval_bases(n, period)[1] == pytest.approx(expected, rel=0, abs=2e-15)
def test_geometry_repeats_exactly_across_cycles(): def test_geometry_repeats_exactly_across_cycles():
A = p.amplitude(20) A = p.amplitude(20)
for m in (0, 1, T // 4, T // 2 - 1, 7 * T // 12): for m in (0, 1, T // 4, T // 2 - 1, 7 * T // 12):
+115
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@@ -0,0 +1,115 @@
"""Research interface contracts; no CUDA context or physical validation."""
import importlib.util
from pathlib import Path
from types import SimpleNamespace
from unittest.mock import patch
import numpy as np
import pytest
ROOT = Path(__file__).resolve().parents[2]
spec = importlib.util.spec_from_file_location('karman_viv_research_driver', ROOT/'research/karman_viv/run.py')
m = importlib.util.module_from_spec(spec)
spec.loader.exec_module(m)
def test_observation_unit_mapping_and_order():
norm = dict(force_norm_fact=2.,sens_deviation=np.arange(6)/10.,sens_norm_fact=np.ones(6)*3)
s=np.arange(6)*.001; f=np.arange(6)*.01
raw,obs,nclip=m.observation(s,f,2,norm)
np.testing.assert_array_equal(raw,np.asarray([*(s*156),*(f*2)],np.float32))
expected=np.hstack((raw[6:]/2,(raw[:6]-np.asarray(norm['sens_deviation'],np.float32))/3))
np.testing.assert_array_equal(obs,expected.astype(np.float32))
assert nclip==0
def test_same_physical_signal_d20_d40():
norm=dict(force_norm_fact=1.,sens_deviation=np.zeros(6),sens_norm_fact=np.ones(6))
a=m.observation(np.ones(6)*.001,np.arange(6)*.01,1,norm)
b=m.observation(np.ones(6)*.0005,np.arange(6)*.005,2,norm)
np.testing.assert_array_equal(a[0],b[0]); np.testing.assert_array_equal(a[1],b[1])
def test_zero_action_and_ccw_scale():
np.testing.assert_array_equal(m.wall_target(-m.BIAS/8,2),np.zeros(3))
np.testing.assert_allclose(m.wall_target(np.ones(3),2),[.04,.02,.06])
assert m.wall_target(np.ones(3),2)[0]/20 == .002
def test_ema_equal_physical_time_and_interval_reset():
target=np.array([.01,-.02,.03]); coarse=np.zeros(3); fine=np.zeros(3)
for _ in range(13): coarse=m.ema(coarse,target,1)
for _ in range(52): fine=m.ema(fine,target,2)
np.testing.assert_allclose(fine,coarse,rtol=2e-15,atol=1e-17)
np.testing.assert_allclose(m.ema(np.zeros(3),target,2),(1-.9**.25)*target)
def test_config_real_parser(tmp_path):
import json
from CelerisLab.config import load_lbm_config
path=tmp_path/'config.json';path.write_text(json.dumps(m.config(40)))
cfg=load_lbm_config(str(path));cfg.validate()
assert (cfg.nx,cfg.ny,cfg.velocity,cfg.viscosity)==(2559,1022,.005,.004)
def test_structure_physical_scaling_and_no_damping():
coarse=m.Structure(2,1e-4,0,20);fine=m.Structure(2,2.5e-5,0,40)
assert fine.mass==4*coarse.mass
assert fine.stiffness==coarse.stiffness/4
assert fine.damping==0
assert fine.candidate(0)==(0.,0.)
def test_observation_clipping_and_nonfinite():
norm=dict(force_norm_fact=1.,sens_deviation=np.zeros(6),sens_norm_fact=np.ones(6))
_,obs,n=m.observation(np.ones(6),np.ones(6),2,norm)
assert n==12 and np.array_equal(obs,np.ones(12,np.float32))
with pytest.raises(RuntimeError,match='nonfinite'):
m.observation(np.full(6,np.nan),np.zeros(6),2,norm)
def test_arm_step_order_and_native_rhs(tmp_path):
import CelerisLab
from CelerisLab.body.motion import MovingTables
from contextlib import nullcontext
log=[];candidates=[]
class Structure:
y=v=0.;mass=2.;stiffness=3.;frequency=.1
def __init__(self,*args): pass
def candidate(self,f):
candidates.append(f)
return self.y+.001,self.v+.002
class Sim:
def __init__(self,*args): self.n=0
def __enter__(self): return self
def __exit__(self,*args): pass
def initialize(self): pass
def set_body(self,p,**kw): log.append(('set',p,kw))
def run(self,n,**kw): self.n+=1;log.append(('run',n,kw))
def moving_diagnostics(self):
a=np.zeros((3,len(MovingTables.DIAG)),np.float32)
a[:,MovingTables.DIAG.index('cme_y')]=self.n
a[:,MovingTables.DIAG.index('wen_y')]=10*self.n
a[:,MovingTables.DIAG.index('cover_jy')]=1000
return a
def read_force(self,p): return [0.,float(self.n),0.]
def read_sensor(self,p): return [.001,0.,0.]
seen=[]
model=SimpleNamespace(predict=lambda obs,**kw:(seen.append(obs.copy()) or np.ones(3)*.1,None))
norm=dict(force_norm_fact=1.,sens_deviation=np.zeros(6),sens_norm_fact=np.ones(6))
with patch.object(CelerisLab,'Simulation',Sim),patch.object(m,'Structure',Structure), \
patch.object(m,'add_scene',return_value=([1,2,3],[4,5,6])),patch.object(m,'install_seed',return_value={}), \
patch.object(m,'check_time'):
m.run_arm('controlled','cfg',2,2,2,None,7.,model,norm,tmp_path,0,1)
assert candidates==[7.,33.,66.,99.] # previous native force, NOT SI mean or node impulse
assert not seen[0].any() and len(seen)==2
assert [e[0] for e in log]==['set','set','set','run']*4
for e in log:
if e[0]=='set': assert e[2]['vy']==pytest.approx(.001) and e[2]['omega']!=0
else: assert e[2]==dict(zero_obs=True,sync_obs=True)
rows=np.load(tmp_path/'controlled/steps.npy')
np.testing.assert_allclose(rows[:,1],[.001,.002,.003,.004])
assert rows.shape==(4,18)
np.testing.assert_array_equal(rows[0,15:],rows[2,15:]) # EMA resets at SI boundary
signals=np.load(tmp_path/'controlled/signals.npz')
np.testing.assert_array_equal(signals['forces'][:,1],[3.,7.]) # interval CME *2, not CME+Wen
+122
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@@ -0,0 +1,122 @@
"""Host admission and independent lattice-stencil checks; no CUDA context."""
from types import SimpleNamespace
import numpy as np
import pytest
from CelerisLab.body.motion import MovingCircle, MovingTables, Translation, validate_shared_translations
from CelerisLab.lbm.descriptors import FLUID
from tests.unit.test_moving_bodies import STREAM, body, moving_simulation, routed_simulation
def scene(monkeypatch, envelope=None, gap=10.):
sim = routed_simulation(monkeypatch)
envelope = envelope or Translation((0., 0., -6., 6.), .5, shared=True)
for y in (40. - (20. + gap) / 2., 40. + (20. + gap) / 2.):
sim.bodies.add(body(60., y, 10., envelope))
sim.field = SimpleNamespace(nx=120, ny=80, build_channel_flags=lambda: np.full((80, 120), FLUID))
return sim
def test_shared_bands_are_admitted_but_other_groups_are_not(monkeypatch):
sim = scene(monkeypatch)
sim._validate_moving_bodies()
a, b = [o.motion for o in sim.bodies.objects]
assert a.band()[3] >= b.band()[2] # whole envelopes genuinely overlap
band, geom = MovingTables.layout([(a, 0), (b, 1)])
assert band[10] == band[2] * band[3] * 8
assert len(geom) == 14
b.translation = Translation((0., 0., -6., 6.), .5, shared=True)
with pytest.raises(ValueError, match='overlaps body'):
sim._validate_moving_bodies() # equal values do not link independent motion
b.translation = a.translation
sim.bodies.add(body(60., 40., 2.))
with pytest.raises(ValueError, match='overlaps body'):
sim._validate_moving_bodies()
@pytest.mark.parametrize('gap', (.3, 4.))
def test_small_surface_gaps_rejected(monkeypatch, gap):
with pytest.raises(ValueError, match='clearance'):
scene(monkeypatch, gap=gap)._validate_moving_bodies()
def test_shared_envelope_is_transverse_only():
with pytest.raises(ValueError, match='transverse'):
Translation((-.1, .1, -1., 1.), .5, shared=True)
envelope = Translation((0., 0., -1., 1.), .5, shared=True)
with pytest.raises(ValueError, match="zero x velocity"):
MovingCircle((0., 0.), 10., envelope).check_target((0., .1), (.1, .1))
def test_group_rejection_is_before_writes_and_can_be_corrected(monkeypatch):
sim, writes = moving_simulation(monkeypatch)
env = Translation((0., 0., -2., 2.), .5, shared=True)
sim.bodies.objects = [body(40., y, 10., env) for y in (20., 50.)]
a, b = [o.motion for o in sim.bodies.objects]
sim.stepper.moving = object()
a.set_target((0., .2), (0., .2))
with pytest.raises(ValueError, match='identical'):
sim.run(1, stream=STREAM)
assert writes == [] and a.applied == b.applied == (0., 0.)
b.set_target((0., .2), (0., .1))
with pytest.raises(ValueError, match='identical'):
sim.run(1, stream=STREAM)
assert writes == []
b.set_target((0., .2), (0., .2))
validate_shared_translations([a, b])
b.applied = (0., -.1)
with pytest.raises(ValueError, match='identical'):
validate_shared_translations([a, b])
C = np.array([(x, y) for x in (-1, 0, 1) for y in (-1, 0, 1) if (x, y) != (0, 0)])
def footprint_conflicts(centres, radius, dy):
"""Enumerate geometric write/read supports, not refill/BFL formulas.
Tests every candidate donor, conservatively including M2's second link.
Body-indexed slot numbers are separate from physical (cell,direction) writes.
"""
centres = np.asarray(centres, float)
lo = np.floor(centres.min(0) - radius - 4).astype(int)
hi = np.ceil(centres.max(0) + radius + 4).astype(int)
yy, xx = np.mgrid[lo[1]:hi[1]+1, lo[0]:hi[0]+1]
points = np.column_stack((xx.ravel(), yy.ravel()))
def inside(p, c):
return ((p - c)**2).sum(axis=-1) < radius**2
old = np.array([inside(points, c) for c in centres])
new_centres = centres + (0., dy)
new = np.array([inside(points, c) for c in new_centres])
changed = old ^ new
conflicts = int(np.count_nonzero(changed.sum(0) > 1))
writes = set()
for i, (oc, nc) in enumerate(zip(centres, new_centres)):
others = [j for j in range(len(centres)) if j != i]
fresh = points[old[i] & ~new[i]]
for e in C:
donor = fresh + e
valid = ~inside(donor, oc) & ~inside(donor, nc)
for j in others:
conflicts += int(np.count_nonzero(valid & (inside(donor, centres[j]) | inside(donor, new_centres[j]))))
link = ~new[i] & inside(points + e, nc)
fluid = points[link]
solid = fluid + e
for p in solid:
slot = (int(p[0]), int(p[1]), int(e[0]), int(e[1]))
conflicts += int(slot in writes)
writes.add(slot)
for read in (fluid, fluid - e):
for j in others:
conflicts += int(np.count_nonzero(inside(read, centres[j]) | inside(read, new_centres[j])))
return conflicts
def test_counterexample_and_pinball_local_ownership():
# Close but disjoint circles are insufficient: parent/Grok independent example.
assert footprint_conflicts(((.25, .25), (.25, 8.55)), 4., .5) > 0
for phase in (0., .25, .5, .75):
for dy in (-.5, -.1, .1, .5):
centres = np.array(((0., 0.), (26., 15.), (26., -15.))) + phase
assert footprint_conflicts(centres, 10., dy) == 0
+128
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@@ -0,0 +1,128 @@
"""Real config loading and pure structural update for the frozen development case."""
import importlib.util
import math
from pathlib import Path
import numpy as np
import pytest
path = Path(__file__).resolve().parents[2] / 'research/steady_pinball/run.py'
spec = importlib.util.spec_from_file_location('steady_pinball_run', path)
runner = importlib.util.module_from_spec(spec)
spec.loader.exec_module(runner)
def test_actual_loader_and_paper_geometry(tmp_path):
import json
from CelerisLab.config import load_lbm_config
p = tmp_path/'config.json'
p.write_text(json.dumps(runner.config()))
cfg = load_lbm_config(str(p))
cfg.validate()
assert (cfg.nx, cfg.ny, cfg.viscosity, cfg.velocity) == (1280, 512, .004, .01)
assert cfg.collision == 'MRT' and cfg.y_wall_bc == 'bounce_back'
assert runner.U * runner.D / runner.NU == 50.
assert runner.CENTRES == ((600., 255.5), (626., 270.5), (626., 240.5))
def test_structure_rest_equilibrium_and_energy_decay():
s = runner.Structure(zeta=.01)
assert s.candidate(0.) == (0., 0.)
assert s.mass == pytest.approx(10*3*math.pi*100)
s.y, s.v = .2, 0.
# One damped period: independent continuous solution at total elapsed time.
for _ in range(runner.PERIOD):
s.y, s.v = s.candidate(0.)
t = runner.PERIOD
a = s.zeta*s.omega
w = s.omega*math.sqrt(1-s.zeta**2)
expected = .2*math.exp(-a*t)*(math.cos(w*t)+a/w*math.sin(w*t))
assert s.y == pytest.approx(expected, abs=2e-12)
assert .5*s.mass*s.v*s.v+.5*s.stiffness*s.y*s.y < .5*s.stiffness*.2**2
s.y, s.v = .3, 0.
assert s.candidate(s.stiffness*.3) == pytest.approx((.3, 0.), abs=1e-15)
def test_report_uses_completed_rows_and_net_force():
rows = np.zeros((4, 15))
rows[:, 0] = np.arange(1, 5)
rows[:, 1] = 2.
rows[:, 3:9] = 1.
got = runner.summarize(rows)
assert got[0]['end_step'] == 4
assert got[0]['y_rms_D'] == .1
assert got[0]['fy_rms'] == 6.
@pytest.mark.parametrize('case', ['Z0', 'M2', 'R2'])
def test_zero_damping_cases_conserve_unforced_energy_and_match_forced_solution(case):
s = runner.Structure(*runner.STRUCTURES[case])
assert s.zeta == s.damping == 0.
s.y, s.v = .2, 1.e-5
y0, v0 = s.y, s.v
energy = .5*s.mass*v0**2 + .5*s.stiffness*y0**2
for _ in range(12345):
s.y, s.v = s.candidate(0.)
assert .5*s.mass*s.v**2 + .5*s.stiffness*s.y**2 == pytest.approx(energy, rel=2e-11)
force, elapsed = 1.e-4, 3210
s.y, s.v = y0, v0
for _ in range(elapsed):
s.y, s.v = s.candidate(force)
phase = s.omega*elapsed
equilibrium = force/s.stiffness
expected_y = equilibrium+(y0-equilibrium)*math.cos(phase)+v0*math.sin(phase)/s.omega
expected_v = -(y0-equilibrium)*s.omega*math.sin(phase)+v0*math.cos(phase)
assert (s.y, s.v) == pytest.approx((expected_y, expected_v), abs=2e-11)
def test_predeclared_comparisons_change_structure_only():
z, m, r = [runner.Structure(*runner.STRUCTURES[k]) for k in ['Z0', 'M2', 'R2']]
assert m.mass/z.mass == pytest.approx(.2)
assert m.stiffness/z.stiffness == pytest.approx(.2)
assert r.mass == m.mass
assert r.stiffness/m.stiffness == pytest.approx(.36)
assert [runner.STEPS*s.frequency for s in [z, m, r]] == pytest.approx([60., 60., 36.])
@pytest.mark.parametrize('diameter', [20, 40, 60])
def test_diffusive_scaling_preserves_physical_geometry_and_duration(tmp_path, diameter):
import json
from CelerisLab.config import load_lbm_config
scale = diameter/20
raw = runner.config(diameter)
p = tmp_path/'scaled.json'
p.write_text(json.dumps(raw))
cfg = load_lbm_config(str(p))
cfg.validate()
assert cfg.velocity*diameter/cfg.viscosity == pytest.approx(50.)
assert (cfg.nx-1)/diameter == 1279/20
assert (cfg.ny-2)/diameter == 510/20
for original, mapped in zip(runner.CENTRES+runner.PROBES,
runner.scaled_points(runner.CENTRES+runner.PROBES, scale)):
assert mapped[0]/diameter == pytest.approx(original[0]/20)
assert (mapped[1]-.5)/diameter == pytest.approx((original[1]-.5)/20)
old = runner.Structure(*runner.STRUCTURES['M2'])
new = runner.Structure(2., old.frequency/scale**2, diameter=diameter)
assert new.mass/old.mass == pytest.approx(scale**2)
assert new.stiffness/old.stiffness == pytest.approx(1/scale**2)
assert new.damping == 0.
assert cfg.velocity/(new.frequency*diameter) == pytest.approx(5.)
assert runner.STEPS*scale**2*cfg.velocity/diameter == pytest.approx(300.)
assert runner.WARMUP*scale**2*cfg.velocity/diameter == pytest.approx(256.)
# A physical held force maps as F_fine=F_coarse/scale in two dimensions.
old.y, old.v = .3, .0002
new.y, new.v = scale*old.y, old.v/scale
expected = old.candidate(.0001)
for _ in range(round(scale**2)):
new.y, new.v = new.candidate(.0001/scale)
assert (new.y/scale, new.v*scale) == pytest.approx(expected, abs=2e-12)
def test_scaled_summary_uses_requested_units_and_completed_rows():
rows = np.zeros((5, 15))
rows[:, 0] = np.arange(1, 6)
rows[:, 1] = 4.
got = runner.summarize(rows, diameter=40, block_steps=3)
assert [(x['start_step'], x['end_step']) for x in got] == [(1, 3), (4, 5)]
assert all(x['y_rms_D'] == .1 for x in got)
assert runner.summarize(rows[:0], diameter=40) == []